Re: [R] permutation test for linear models with continuous covariates

From: Peter Dalgaard <p.dalgaard_at_biostat.ku.dk>
Date: Thu 01 Dec 2005 - 01:11:45 EST

"anders superanders" <andersdetermigigen@hotmail.com> writes:

> Hi I was wondering if there is a permutation test available in R for linear
> models with continuous dependent covariates. I want to do a test like the
> one shown here.
>
> bmi<-rnorm(100,25)
> x<-c(rep(0,75),rep(1,25))
> y<-rnorm(100)+bmi^(1/2)+rnorm(100,2)*x+bmi*x
>
> H0<-lm(y~1+x+bmi)
> H1<-lm(y~1+x+bmi+x*bmi)
> anova(H0,H1)
> summary(lm(y~1+x+bmi))
>
>
> But I want to use permutation testing to avoid an inflated p-value due to a
> y that is not totally normal distributed and I do not want to log transform
> y.

Er, what would you permute? For an interaction test like this (notice by the way that "*" in your model formula does not mean what you think it does) I do not think a permutation test exists. You could try bootstrapping to get an improved approximation the distribution of the interaction term.

-- 
   O__  ---- Peter Dalgaard             ุster Farimagsgade 5, Entr.B
  c/ /'_ --- Dept. of Biostatistics     PO Box 2099, 1014 Cph. K
 (*) \(*) -- University of Copenhagen   Denmark          Ph:  (+45) 35327918
~~~~~~~~~~ - (p.dalgaard@biostat.ku.dk)                  FAX: (+45) 35327907

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Received on Thu Dec 01 02:07:06 2005

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